Mohan Rajendran
Senior Software Engineer - AWS Elasticache at Amazon Web Services (AWS)
Seattle, Washington, United States
Summary
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Senior🎓
Top SchoolMohan Rajendran is a Senior Software Development Engineer with 14 years of experience building scalable systems across domains from oil-and-gas simulations to eCommerce advertising and consumer photo storage. At Amazon he has designed low-latency ad retrieval and recommendation services that process terabyte-scale data and contributed to Amazon Photos’ content management for secure, cost-effective storage. He spans the full stack—front-end, back-end, and data pipelines—using Java, Kotlin, Scala, Python, Spark and a wide range of AWS services to deliver high-availability, fault-tolerant systems. His background in computational science and C++ research informs practical machine-learning contributions, including implementing Non-negative Matrix Factorization in the well-regarded mlpack library. Colleagues know him for translating research prototypes into production microservices and for mentoring engineers while establishing sound DevOps and change-management practices. Based in Seattle, he combines rigorous academic training with a hands-on appetite for new technologies to solve complex business problems.
14 years of coding experience
14 years of employment as a software developer
BE Aeronautical Engineering, BE Aeronautical Engineering at Madras Institute of TechnologyMS Computational Science and Engineering, MS Computational Science and Engineering at Georgia Institute of TechnologyGCSE A Level Maths, GCSE A Level Maths at Victoria Junior CollegeO Level, O Level at Raffles Institution
English, Tamil, French, Japanese, Spanish
Github Skills (7)
machine-learning10
c-language10
cpp10
cprogramming-language10
cplus10
regression7
deep-learning4
Programming languages (5)
Github contributions (5)
mlpack/mlpack
Jun 2012 - Aug 2012
mlpack: a fast, header-only C++ machine learning library
Role in this project:
ML Engineer
ML EngineerContributions:10 commits in 1 month
Contributions summary:Mohan implemented a basic version of Non-negative Matrix Factorization (NMF) in the mlpack library. This involved defining the NMF class and the required update rules. The user's work focused on creating and integrating different update methods for the W and H matrices. Unit tests were also created to validate the NMF implementation.
cppmachine-learningmlpackmachine-learning-libraryc-plus-plus
mohanrajendran/mohanrajendran.github.io
Jan 2015 - Mar 2026
Contributions:26 pushes in 11 years 4 months
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